CoRe-MoE: Contrastive Reweighted Mixture of Experts for Multi-Terrain Humanoid Locomotion with Gait Adaptation
arXiv:2606.04718v1 Announce Type: cross Abstract: Humans primarily rely on walking and running to traverse complex terrains, without resorting to unnecessarily complex motion patterns. Similarly, humanoid robots should achieve smooth transitions between walking and running while maintaining natural and stable locomotion. However, unifying gait transition and multi-terrain adaptation within a single policy remains challenging due to gradient interference and the distribution shift induced by terrain-dependent visual and dynamic variations. Although Mixture-of-Experts (MoE) architectures can all
The proliferation of humanoid robot research and development is accelerating, fueled by advances in AI and robotics, making solutions for complex locomotion critical.
Achieving robust, adaptive locomotion for humanoid robots across varied terrains is a critical bottleneck to their widespread commercial and industrial deployment.
This research presents a significant step towards general-purpose humanoid robots that can seamlessly navigate diverse environments, including outdoor and industrial settings.
- · Humanoid robotics manufacturers
- · Logistics and industrial sectors
- · AI and machine learning developers
- · Tasks requiring manual human inspection in dangerous terrains
More capable and versatile humanoid robots will emerge, expanding their potential applications beyond controlled environments.
Increased adoption of humanoid robots in logistics, disaster response, and exploration could lead to new economic models and labor market shifts.
The development of highly adaptive humanoid robots could accelerate breakthroughs in prosthetics and exoskeletons, improving human capabilities.
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Read at arXiv cs.AI